Anson McCade
Lead AI Engineer
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An exciting opportunity is available for an experienced Lead AI Engineer to drive the development and deployment of cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) solutions within a market-leading Workday product portfolio.
Working at the intersection of AI engineering, software development and MLOps, the successful candidate will be responsible for transforming machine learning models into secure, scalable, production-ready applications. Collaborating closely with data scientists, software engineers, and product specialists, they will help deliver innovative AI-powered capabilities that enhance enterprise Workday solutions.
This role is ideally suited to an experienced engineer with a passion for building robust AI systems, leveraging cloud technologies, and integrating intelligent solutions into enterprise-grade software platforms.
Key Responsibilities
- Design, develop, and deploy production-ready AI and machine learning solutions that are scalable, resilient, and high performing.
- Partner with cross-functional teams including data science, engineering, and product management to deliver AI-powered features and capabilities.
- Integrate machine learning models into enterprise software products while ensuring reliability, maintainability, and operational excellence.
- Build and optimize AI deployment pipelines using modern MLOps practices, including automated testing, continuous integration, continuous deployment (CI/CD), model versioning, and monitoring.
- Develop cloud-native AI solutions using industry-leading platforms and services.
- Create and maintain robust data pipelines to support AI workloads, enabling efficient data processing and seamless integration with enterprise systems.
- Champion engineering best practices, code quality, and continuous improvement across AI development initiatives.
- Contribute to architectural decisions that support the long-term scalability and evolution of AI-enabled products.
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Essential Skills & Experience
- Extensive commercial experience in software engineering with strong programming skills in Python, Java, and/or C++.
- Demonstrable success deploying AI and Machine Learning models into production environments with a focus on scalability, reliability, and performance.
- Strong understanding of MLOps, including CI/CD pipelines, model lifecycle management, monitoring, and automated deployment.
- Hands-on experience with major cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP) together with cloud-native AI services such as Amazon SageMaker, Azure Machine Learning, or Vertex AI.
- Experience using Docker, Kubernetes, and containerized application architectures to deploy and manage AI workloads.
- Excellent data engineering skills, including designing data pipelines, data transformation, and integration with enterprise data platforms.
- Experience working within Agile software development environments.
- Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into practical business solutions while collaborating effectively across multidisciplinary teams.
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Desirable Experience
- Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related discipline.
- Experience working with Workday APIs, integrations, and data models.
- Practical experience designing and implementing Generative AI solutions using Large Language Models (LLMs) such as OpenAI GPT or Hugging Face Transformers.
- Strong understanding of deep learning techniques including Transformers, CNNs, and RNNs, with experience applying these technologies to real-world business challenges.
- Active involvement within the AI community through conferences, technical publications, blogs, workshops, or open-source contributions.
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